PD52-02 HUMAN VOLATILOME ANALYSIS OF PATIENTS WITH RENAL CELL CARCINOMA: PROSPECTIVE, TWO-ARM NON-RANDOMIZED MONOCENTRIC STUDY

You have accessJournal of UrologyKidney Cancer: Epidemiology & Evaluation/Staging/Surveillance II (PD52)1 Sep 2021PD52-02 HUMAN VOLATILOME ANALYSIS OF PATIENTS WITH RENAL CELL CARCINOMA: PROSPECTIVE, TWO-ARM NON-RANDOMIZED MONOCENTRIC STUDY Alessio Filianoti, Manuela Costantini, Umberto Anceschi, Alfredo Maria Bove, Aldo Brassetti, Consilia Ferriero, Riccardo Mastroianni, Leonardo Misuraca, Gabriele Tuderti, Gennaro Ciliberto, and Giuseppe Simone FilianotiAlessio Filianoti More articles by this author , CostantiniManuela Costantini AnceschiUmberto Anceschi BoveAlfredo Bove BrassettiAldo Brassetti FerrieroMaria Ferriero MastroianniRiccardo Mastroianni MisuracaLeonardo Misuraca TudertiGabriele Tuderti CilibertoGennaro Ciliberto SimoneGiuseppe View All Author Informationhttps://doi.org/10.1097/JU.0000000000002079.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Urine analysis electronic (e)-nose technology provides volatile organic compounds (VOCs) molecular profiles that shown potential in the diagnosis non-urological diseases. Few works suggested dogs trained smell urine could recognize lung, bladder, or breast cancer with various success rates, but no date are available diagnostic setting renal cell carcinoma (RCC). In study, we investigated urinary VOCs profiling discriminating patients established RCC from healthy controls. METHODS: This prospective study included 2 groups: 115 controls (HC) 98 cases. samples were collected twice then sampled a commercially nose (Cyranose C320 – 32 sensors). Data reduced set principal components capturing largest amount variance original sensors (Principal [PCA]). Univariate was used select best be entered into linear Canonical Discriminant Analysis (CDA) classify cases categorical partition. We “leave-one-out method” calculate Cross Validated Accuracy (CVA), an estimate accuracy predictive model clinical practice. For each case probability positive calculated on basis CDA function. Discrimination built evaluated means receiver operator characteristics (ROC) curves. RESULTS: Based PCA, 83/98 99/115 correctly identified eNose arms, respectively. Results obtained demonstrated correct classification 85.4% (p <0.001). At ROC discrimination between 0.907. Repeated using second measure sample provided comparable findings (CVA 85.1% ROC-curve 0.89). Sensitivity specificity 84.7% 86.1, respectively; likelihood ratio (+LR) negative (-LR) 6.09 0.18, CONCLUSIONS: Preliminary pilot highlights for future research eNose. Ease use, low costs non-invasive nature makes test biomarker different settings, follow-up. Source Funding: NONE © 2021 American Urological Association Education Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e911-e911 Advertisement Copyright Permissions© Inc.MetricsAuthor Information Expand Loading ...